Example #1
0
def first():
    data = scrape_top_list()
    for i in data:
        movie_url = i['url']
        cast_link = movie_url + 'fullcredits#cast'
        linked_Data = link_movie(movie_url, cast_link)
        total_data_list.append(linked_Data)
    js = json.dumps(total_data_list, indent=4, sort_keys=True)
    with open("Total_movie_list_with_casts.json",
              "w") as q:  # Total movies List of 250 movies
        q.write(js)
Example #2
0
## In this task, I have counted all the movies that have been released in Hindi, English and Malayalam languages.

from Task5 import get_movie_list_details
from Task1 import scrape_top_list
movies_list = scrape_top_list()
top_ten_movie = movies_list[:250]

def analyse_movies_language(how_many_movies):
    allmovies = get_movie_list_details(how_many_movies)
    hindi = 0
    english = 0
    malayalam = 0
    for each_movie in allmovies:
        # print (allmovies)
        lang_list = each_movie['Language']
        for i in lang_list:
            if i == "Hindi":
                hindi += 1
            elif i == "English":
                english += 1
            elif i == "Malayalam":
                malayalam+=1
    lang_dic = {'Hindi': hindi, 'English': english, 'Malayalam': malayalam}
    return (lang_dic)
print (analyse_movies_language(top_ten_movie))
Example #3
0
from Task1 import scrape_top_list
import requests
import json
from bs4 import BeautifulSoup
from pprint import pprint

name1 = scrape_top_list()
year = []


def group_by_decade():
    i = 0
    while i < len(name1):
        year.append(name1[i]["year"])
        i = i + 1
    year.sort()
    j = 0
    my_dict = {}
    while j < len(year):
        dec = (year[j] // 10) * 10
        k = 0
        decade = []
        while k < len(name1):
            if name1[k]["year"] >= dec and name1[k]["year"] < (dec + 10):
                decade.append(name1[k])
            my_dict[dec] = decade
            k = k + 1
        j = j + 1
        with open("decade_vise_movie.json", "w") as saral_data3:
            json.dump(my_dict, saral_data3, indent=4)
Example #4
0
def funfirst():
    data1 = scrape_top_list()
    for i in data1:
        castLink = i['url'] + 'fullcredits#cast'
        casting(castLink)
Example #5
0
        time = soup.find("div",class_="subtext")
        runtime = time.find("time").get_text().strip()
        hour_in_min = (int(runtime[0])) *60
        i = 0
        mins = ""
        b = (runtime[3:])
        while i < len(b):
            if b[i] == "m":
                break
            mins = mins + b[i]
            i = i + 1
        runtime_of_movie = hour_in_min + int(mins)
        movie_genre = time.find_all("a")
        movie_genre.pop()
        for i in movie_genre:
            genre = i.get_text()
            gen.append(genre)
        details["movie_name"] = name1["name"]
        details["director"] = dire
        details["country"] = "India"
        details["poster_url"] = movie_poster
        details["language"] = lang
        details["movie_bio"] = movie_bio
        details["runtime"] = runtime_of_movie
        details["movie_genre"] = gen
        list1.append(details.copy())
        with open("10movies_details.json","w") as movie:
            json.dump(list1,movie,indent=4)
    return(list1)
top_movie_list = movies_details(scrape_top_list())